Accurate Prediction of Response to Interferon-based Therapy in Egyptian Patients with Chronic Hepatitis C Using Machine-learning Approaches

Hepatitis C virus' patients with genotypes 1 & 4 have break-even response rates to Pegylated-Interferon (Peg-IFN) and Ribavirin (RBV) treatment. Furthermore, the incompliance to the treatment because of its high cost and related unfavorable effects makes its prediction of paramount importan...

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Bibliographische Detailangaben

Hauptverfasser:	ElHefnawi, M., Abdalla, M., Ahmed, S., Elakel, W., Esmat, G., Elraziky, M., Khamis, S., Hassan, M.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Accuracy Artificial neural networks Data mining Decision tree Decision trees HCV machine-learning Mathematical model Medical treatment Peg-interferon response to therapy Sensitivity and specificity Training
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